PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?property ( SAMPLE( ?plabel ) AS ?label ) ( COUNT( ?o ) AS ?count ) WHERE {
  ?item wdt:P31 wd:Q40231 .
  ?item ?p ?o .
  FILTER ( STRSTARTS( STR( ?p ) , "http://www.wikidata.org/prop/direct/" ) ) BIND( IRI( REPLACE( STR( ?p ) , "http://www.wikidata.org/prop/direct/" , "http://www.wikidata.org/entity/" ) ) AS ?property ) OPTIONAL {
    ?property rdfs:label ?plabel .
    FILTER ( LANG( ?plabel ) = "en" )
  }
}
GROUP BY ?property
ORDER BY DESC ( ?count )
LIMIT 500

Got 159 rows and 3 columns, showing the first 5 and last 5 rows below:
| property                                          | label                                       | count           |
| ------------------------------------------------- | ------------------------------------------- | --------------- |
| instance of (wd:P31)                              | instance of (en)                            | 24894 (xsd:int) |
| natural type (wd:P31279)                          | natural type (en)                           | 24412 (xsd:int) |
| country (wd:P17)                                  | country (en)                                | 20034 (xsd:int) |
| point in time (wd:P585)                           | point in time (en)                          | 13237 (xsd:int) |
| candidate (wd:P726)                               | candidate (en)                              | 10863 (xsd:int) |
| ...                                               | ...                                         | ...             |
| age of candidacy (wd:P2998)                       | age of candidacy (en)                       | 1 (xsd:int)     |
| National Library of Wales Authority ID (wd:P2966) | National Library of Wales Authority ID (en) | 1 (xsd:int)     |
| day of week (wd:P2894)                            | day of week (en)                            | 1 (xsd:int)     |
| country of citizenship (wd:P27)                   | country of citizenship (en)                 | 1 (xsd:int)     |
| IdRef ID (wd:P269)                                | IdRef ID (en)                               | 1 (xsd:int)     |

I ran a query that: 1) finds items that are instance of public election (wd:Q40231), 2) collects all direct properties used on those items, and 3) counts how often each property occurs.

Top results (property - count):
- wd:P31 (instance of) - 24894
- wd:P31279 (natural type) - 24412
- wd:P17 (country) - 20034
- wd:P585 (point in time) - 13237
- wd:P726 (candidate) - 10863

The query returns 159 distinct properties in total (limited to 500 results). The full SPARQL query is included above and returns the property IRIs, their English labels (if any), and counts.

Which properties are used in claims related to items that are public elections? Include a count of the number of times it was used.

[System]
You are a question answering assistant. Your job is to generate a SPARQL query to answer a given user question.

You have access to the following knowledge graphs:
wikidata at https://qlever.cs.uni-freiburg.de/api/wikidata-sebastian

You are provided with some general notes:
No notes available

You can use the following SPARQL prefixes implicitly in all functions:
cc: <http://creativecommons.org/ns#
data: <https://www.wikidata.org/wiki/Special:EntityData/
dct: <http://purl.org/dc/terms/
geo: <http://www.opengis.net/ont/geosparql#
geof: <http://www.opengis.net/def/function/geosparql/
imdb: <https://www.imdb.com/
math: <http://www.w3.org/2005/xpath-functions/math#
ontolex: <http://www.w3.org/ns/lemon/ontolex#
owl: <http://www.w3.org/2002/07/owl#
p: <http://www.wikidata.org/prop/
pq: <http://www.wikidata.org/prop/qualifier/
pqn: <http://www.wikidata.org/prop/qualifier/value-normalized/
pqv: <http://www.wikidata.org/prop/qualifier/value/
pr: <http://www.wikidata.org/prop/reference/
prn: <http://www.wikidata.org/prop/reference/value-normalized/
prov: <http://www.w3.org/ns/prov#
prv: <http://www.wikidata.org/prop/reference/value/
ps: <http://www.wikidata.org/prop/statement/
psn: <http://www.wikidata.org/prop/statement/value-normalized/
psv: <http://www.wikidata.org/prop/statement/value/
qfn: <http://qlever.cs.uni-freiburg.de/function#
ql: <http://qlever.cs.uni-freiburg.de/builtin-functions/
qlss: <https://qlever.cs.uni-freiburg.de/spatialSearch/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
ref: <http://www.wikidata.org/reference/
s: <http://www.wikidata.org/entity/statement/
schema: <http://schema.org/
skos: <http://www.w3.org/2004/02/skos/core#
v: <http://www.wikidata.org/value/
wd: <http://www.wikidata.org/entity/
wdno: <http://www.wikidata.org/prop/novalue/
wdt: <http://www.wikidata.org/prop/direct/
wdtn: <http://www.wikidata.org/prop/direct-normalized/
wikibase: <http://wikiba.se/ontology#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
dc: <http://purl.org/dc/elements/1.1/
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
qb: <http://purl.org/linked-data/cube#
void: <http://rdfs.org/ns/void#

You should follow a step-by-step approach to generate the SPARQL query:
1. Determine possible entities and properties implied by the user question.
2. Search for the entities and properties in the knowledge graphs. Where applicable, constrain the searches with already identified entities and properties.
3. Gradually build up the SPARQL query using the identified entities and properties. Start with simple queries and add more complexity as needed. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

Additional rules:
1. Explain your thought process before and after each step and function call.
2. Do not just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
3. Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
4. The SPARQL query should always return the actual identifiers / IRIs of the items in its result. It additionally may return labels or other human-readable information, but they are optional and should be put within optional clauses unless explicitly requested by the user.
5. Do not stop early if there are still obvious improvements to be made to the SPARQL query. For example, keep refining your SPARQL query if its result contains irrelevant items or is missing items you expected.
6. Do not perform additional computation (e.g. filtering, sorting, calculations) on the result of the SPARQL query to determine the answer. All computation should be done solely within SPARQL.
7. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
8. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] Which properties are used in claims related to items that are public elections? Include a count of the number of times it was used.

[Assistant] Step 1: I'll search Wikidata for the entity corresponding to "public election" to find the correct item identifier. I will call the search_entity tool next.

[Tool]
Top 10 entity alternatives:
1. public election, also known as election, elections (wd:Q40231)
2. Public election committee (wd:Q127273596)
3. Public Offices Election Act (wd:Q11392186): instance of election act, instance of law of Japan, instance of statute
4. Public Official Election Act (wd:Q12592014): instance of Act of South Korea, instance of statute, South Korean law
5. Election publication praised (wd:Q95492900): instance of scholarly article
6. 2009 New York City Public Advocate election, also known as 2009 NYC Public Advocate election, New York City Public Advocate election, 2009 (wd:Q7013284): instance of public election
7. 2019 New York City Public Advocate election, also known as 2019 NYC Public Advocate election (wd:Q85732015): instance of public election
8. 2021 New York City Public Advocate election, also known as 2021 NYC Public Advocate election (wd:Q106651975): instance of public election
9. 2013 New York City Public Advocate election, also known as 2013 NYC Public Advocate election, New York City Public Advocate election, 2013 (wd:Q17091644): instance of public election
10. 2017 New York City Public Advocate election, also known as 2017 NYC Public Advocate election, New York City Public Advocate election, 2017 (wd:Q43078961): instance of public election

[Assistant] I'll first check how many Wikidata items are instances of "public election" (wd:Q40231) to understand the scope. I'll run a simple COUNT query. Then I'll run the main query that lists properties used in statements about those items and count their occurrences. Now I'll execute the count query.

[Tool]
Got 1 row and 1 column:
| count           |
| --------------- |
| 24412 (xsd:int) |

[Assistant] Now I'll run a SPARQL query that finds all properties used as direct claims (wdt:) on items that are instances of public election (wd:Q40231), converts those direct-property IRIs to property entity IRIs (wd:P...), gets an English label if available, and counts how many times each property is used. I'll execute that query now.

[Tool]
SPARQL execution failed:
Invalid SPARQL query: The target ?label of an AS clause was already used in the query body.

[Assistant] Now I'll run the corrected SPARQL query that maps direct-property IRIs to property entity IRIs, gets an English label (if any), and counts occurrences across items that are instances of public election (wd:Q40231).

[Tool]
Got 159 rows and 3 columns, showing the first 5 and last 5 rows below:
| property                                          | label                                       | count           |
| ------------------------------------------------- | ------------------------------------------- | --------------- |
| instance of (wd:P31)                              | instance of (en)                            | 24894 (xsd:int) |
| natural type (wd:P31279)                          | natural type (en)                           | 24412 (xsd:int) |
| country (wd:P17)                                  | country (en)                                | 20034 (xsd:int) |
| point in time (wd:P585)                           | point in time (en)                          | 13237 (xsd:int) |
| candidate (wd:P726)                               | candidate (en)                              | 10863 (xsd:int) |
| ...                                               | ...                                         | ...             |
| age of candidacy (wd:P2998)                       | age of candidacy (en)                       | 1 (xsd:int)     |
| National Library of Wales Authority ID (wd:P2966) | National Library of Wales Authority ID (en) | 1 (xsd:int)     |
| day of week (wd:P2894)                            | day of week (en)                            | 1 (xsd:int)     |
| country of citizenship (wd:P27)                   | country of citizenship (en)                 | 1 (xsd:int)     |
| IdRef ID (wd:P269)                                | IdRef ID (en)                               | 1 (xsd:int)     |

[Assistant] The query succeeded and returned properties used on items that are instances of public election, along with counts. Now I'll prepare the final answer: include the SPARQL query and summarize results. Per instructions, I must explain my thought process before and after each step and function call; I've already done that. Now I'll return the final SPARQL query and the answer summarizing top properties.

[Tool] Stopped generation process


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX p: <http://www.wikidata.org/prop/>
PREFIX pq: <http://www.wikidata.org/prop/qualifier/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX ps: <http://www.wikidata.org/prop/statement/>
SELECT ?org ?orgLabel ?year ( MAX( ?count ) AS ?students ) WHERE {
  ?org wdt:P6782 "024z2rq82" .
  OPTIONAL {
    ?org rdfs:label ?orgLabel FILTER ( LANG( ?orgLabel ) = "en" )
  }
  ?org p:P2196 ?stmt .
  ?stmt ps:P2196 ?count .
  ?stmt pq:P585 ?time .
  BIND( YEAR( ?time ) AS ?year )
}
GROUP BY ?org ?orgLabel ?year
ORDER BY ?year

Got 24 rows and 4 columns, showing the first 5 and last 5 rows below:
| org                                   | orgLabel                      | year           | students            |
| ------------------------------------- | ----------------------------- | -------------- | ------------------- |
| University of Düsseldorf (wd:Q317032) | University of Düsseldorf (en) | 1998 (xsd:int) | 23997 (xsd:decimal) |
| University of Düsseldorf (wd:Q317032) | University of Düsseldorf (en) | 1999 (xsd:int) | 24789 (xsd:decimal) |
| University of Düsseldorf (wd:Q317032) | University of Düsseldorf (en) | 2000 (xsd:int) | 24868 (xsd:decimal) |
| University of Düsseldorf (wd:Q317032) | University of Düsseldorf (en) | 2001 (xsd:int) | 25537 (xsd:decimal) |
| University of Düsseldorf (wd:Q317032) | University of Düsseldorf (en) | 2002 (xsd:int) | 25220 (xsd:decimal) |
| ...                                   | ...                           | ...            | ...                 |
| University of Düsseldorf (wd:Q317032) | University of Düsseldorf (en) | 2017 (xsd:int) | 35343 (xsd:decimal) |
| University of Düsseldorf (wd:Q317032) | University of Düsseldorf (en) | 2018 (xsd:int) | 36575 (xsd:decimal) |
| University of Düsseldorf (wd:Q317032) | University of Düsseldorf (en) | 2019 (xsd:int) | 37540 (xsd:decimal) |
| University of Düsseldorf (wd:Q317032) | University of Düsseldorf (en) | 2020 (xsd:int) | 36070 (xsd:decimal) |
| University of Düsseldorf (wd:Q317032) | University of Düsseldorf (en) | 2021 (xsd:int) | 33942 (xsd:decimal) |

The ROR ID 024z2rq82 corresponds to University of Düsseldorf (wd:Q317032). Student counts by year (year — students):
1998 — 23997
1999 — 24789
2000 — 24868
2001 — 25537
2002 — 25220
2003 — 25224
2004 — 18257
2005 — 19577
2006 — 20014
2007 — 20839
2008 — 21122
2009 — 16794
2010 — 17094
2011 — 23286
2012 — 23511
2013 — 30006
2014 — 32611
2015 — 32050
2016 — 33716
2017 — 35343
2018 — 36575
2019 — 37540
2020 — 36070
2021 — 33942

How many students did the educational organization with the Research Organization Registry (ROR) ID "024z2rq82" have each year? Please include a count for each year (if available), and order results by year.

[System]
You are a question answering assistant. Your job is to generate a SPARQL query to answer a given user question.

You have access to the following knowledge graphs:
wikidata at https://qlever.cs.uni-freiburg.de/api/wikidata-sebastian

You are provided with some general notes:
No notes available

You can use the following SPARQL prefixes implicitly in all functions:
cc: <http://creativecommons.org/ns#
data: <https://www.wikidata.org/wiki/Special:EntityData/
dct: <http://purl.org/dc/terms/
geo: <http://www.opengis.net/ont/geosparql#
geof: <http://www.opengis.net/def/function/geosparql/
imdb: <https://www.imdb.com/
math: <http://www.w3.org/2005/xpath-functions/math#
ontolex: <http://www.w3.org/ns/lemon/ontolex#
owl: <http://www.w3.org/2002/07/owl#
p: <http://www.wikidata.org/prop/
pq: <http://www.wikidata.org/prop/qualifier/
pqn: <http://www.wikidata.org/prop/qualifier/value-normalized/
pqv: <http://www.wikidata.org/prop/qualifier/value/
pr: <http://www.wikidata.org/prop/reference/
prn: <http://www.wikidata.org/prop/reference/value-normalized/
prov: <http://www.w3.org/ns/prov#
prv: <http://www.wikidata.org/prop/reference/value/
ps: <http://www.wikidata.org/prop/statement/
psn: <http://www.wikidata.org/prop/statement/value-normalized/
psv: <http://www.wikidata.org/prop/statement/value/
qfn: <http://qlever.cs.uni-freiburg.de/function#
ql: <http://qlever.cs.uni-freiburg.de/builtin-functions/
qlss: <https://qlever.cs.uni-freiburg.de/spatialSearch/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
ref: <http://www.wikidata.org/reference/
s: <http://www.wikidata.org/entity/statement/
schema: <http://schema.org/
skos: <http://www.w3.org/2004/02/skos/core#
v: <http://www.wikidata.org/value/
wd: <http://www.wikidata.org/entity/
wdno: <http://www.wikidata.org/prop/novalue/
wdt: <http://www.wikidata.org/prop/direct/
wdtn: <http://www.wikidata.org/prop/direct-normalized/
wikibase: <http://wikiba.se/ontology#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
dc: <http://purl.org/dc/elements/1.1/
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
qb: <http://purl.org/linked-data/cube#
void: <http://rdfs.org/ns/void#

You should follow a step-by-step approach to generate the SPARQL query:
1. Determine possible entities and properties implied by the user question.
2. Search for the entities and properties in the knowledge graphs. Where applicable, constrain the searches with already identified entities and properties.
3. Gradually build up the SPARQL query using the identified entities and properties. Start with simple queries and add more complexity as needed. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

Additional rules:
1. Explain your thought process before and after each step and function call.
2. Do not just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
3. Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
4. The SPARQL query should always return the actual identifiers / IRIs of the items in its result. It additionally may return labels or other human-readable information, but they are optional and should be put within optional clauses unless explicitly requested by the user.
5. Do not stop early if there are still obvious improvements to be made to the SPARQL query. For example, keep refining your SPARQL query if its result contains irrelevant items or is missing items you expected.
6. Do not perform additional computation (e.g. filtering, sorting, calculations) on the result of the SPARQL query to determine the answer. All computation should be done solely within SPARQL.
7. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
8. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] How many students did the educational organization with the Research Organization Registry (ROR) ID "024z2rq82" have each year? Please include a count for each year (if available), and order results by year.

[Assistant] Step 1: I'll search Wikidata for an entity with the ROR ID "024z2rq82" to determine the corresponding Wikidata item and confirm which property stores ROR IDs. I'll run a search for the string "024z2rq82". I'll explain the findings and then build the SPARQL query to retrieve the number of students per year for that organization.

[Tool] No entity items found

[Tool]
Top 10 property alternatives:
1. ROR ID, also known as Research Organization Registry ID, ror.org ID (wd:P6782 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): identifier for the Research Organization Registry
2. Gateway to Research organisation ID, also known as GtR ID, UK Research and Innovation organisation ID, UKRI ID (wd:P8501 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): identifier for an organisation in the UK Research and Innovation (UKRI)'s Gateway to Research (GtR) database of research funding
3. Google Scholar organization ID, also known as Google Scholar organisation ID, Google Scholar org ID (wd:P11961 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): numeric identifier for an organisation in Google Scholar
4. Research Resource Identifier, also known as RRID, SciCrunch identifier (wd:P9712 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): identifier in the SciCrunch database of research resources
5. research site, also known as location of research, place researched, research location, site of research, study location (wd:P6153 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): place where this item was researched
6. catalog, also known as registry, exhibition catalogue, catalogue, cat. (wd:P972 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): catalog for the item, or, as a qualifier of P528 – catalog for which the 'catalog code' is valid, subproperty of part of
7. ROARMAP ID, also known as Registry of Open Access Repository Mandates and Policies ID (wd:P4203 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): identifier in the Registry of Open Access Repository Mandates and Policies
8. UIA Open Yearbook organization website ID, also known as YBIO org id, Yearbook of International Organizations (YBIO) org id, Union of International Associations (UIA) org id, Open Yearbook org id, Global Civil Society Database org id (wd:P11915 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): identifier for an international non-governmental organization (I...governmental organizations (IGO) on the UIA Open Yearbook org id
9. Scopus affiliation ID, also known as Scopus organisation ID, Scopus organization ID (wd:P1155 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): identifier for an organisation in author affiliations per Scopus
10. HCERES organisation ID, also known as HCERES ID, High Council for the Evaluation of Research and Higher Education ID (wd:P12613 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): identifier for an organisation on the website of High Council for the Evaluation of Research and Higher Education

[Assistant] I'll search for entities that have property P6782 (ROR ID) with the value "024z2rq82".

[Tool]
Falling back to an unconstrained search on the full search indices due to an error:
Got more than the maximum supported number of object candidates (65,536)

No entity items found

No other items found

No literal items found

[Tool]
Falling back to an unconstrained search on the full search indices due to an error:
Got more than the maximum supported number of object candidates (65,536)

No entity items found

No other items found

No literal items found

[Assistant] I'll run a SPARQL query to find the Wikidata item with P6782 equal to the ROR ID "024z2rq82".

[Tool]
Got 1 row and 2 columns:
| item                                  | itemLabel                     |
| ------------------------------------- | ----------------------------- |
| University of Düsseldorf (wd:Q317032) | University of Düsseldorf (en) |

[Assistant] I'll search for the Wikidata property for "number of students".

[Tool]
Top 10 property alternatives:
1. count of students, also known as count of pupils, count of students, enrollment, number of pupils, number of pupils or students (wd:P2196 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): number of pupils or students of any type in an educational organ...evious years normal rank (not deprecated rank). Don't overwrite.
2. student, also known as pupil, teacher to, teacher of, students, pupils (wd:P802 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): notable student(s) of the subject individual, subproperty of significant person
3. number of out-of-school children (wd:P2573 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): number of out-of-school children reported for a place
4. number of teachers, also known as count of teachers, faculty count (wd:P10610 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): number of teachers at an educational facility
5. school class, also known as stage, school cohort, grade, class, cohort (wd:P7174 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): (qualifier) class of a given year/time period to which the person belonged in an educational institution
6. number of children, also known as number of offspring, number of kids, no. of children, no of children, issue (wd:P1971 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): number of children of the person, animal, or character
7. educated at, also known as graduate of, place of education, school attended, schooled at, college attended (wd:P69 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): educational institution attended by subject, subproperty of affiliation
8. student retention rate (wd:P11698 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): proportion of first-year students at the educational institution who return for their second year
9. number of participants, also known as qty participants, number of competitors, participants, participant count, number of teams (wd:P1132 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): number of participants of an event, e.g. people or groups of people that take part in the event (NO units), subproperty of quantity
10. educational stage, also known as student classification (wd:P7374 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): educational stage of a specific school; qualifier of "educated at" (P69): the education stage of someone's attendance of school

[Assistant] The relevant property seems to be P2196 "count of students". I'll query the University of Düsseldorf (wd:Q317032) for P2196 statements and include the point in time qualifier (P585) which indicates the year/date for the count. I'll build a query to retrieve the year (extracted from P585) and the student count. Then I'll order by year.

[Tool]
Got 31 rows and 2 columns, showing the first 5 and last 5 rows below:
| count               | pointInTime                         |
| ------------------- | ----------------------------------- |
| 36070 (xsd:decimal) | 2020-01-01T00:00:00Z (xsd:dateTime) |
| 23511 (xsd:decimal) | 2012-01-01T00:00:00Z (xsd:dateTime) |
| 36571 (xsd:decimal) | 2018-01-01T00:00:00Z (xsd:dateTime) |
| 35292 (xsd:decimal) | 2017-01-01T00:00:00Z (xsd:dateTime) |
| 32050 (xsd:decimal) | 2015-01-01T00:00:00Z (xsd:dateTime) |
| ...                 | ...                                 |
| 33716 (xsd:decimal) | 2016-01-01T00:00:00Z (xsd:dateTime) |
| 16794 (xsd:decimal) | 2009-01-01T00:00:00Z (xsd:dateTime) |
| 17094 (xsd:decimal) | 2010-01-01T00:00:00Z (xsd:dateTime) |
| 33715 (xsd:decimal) | 2016-01-01T00:00:00Z (xsd:dateTime) |
| 18257 (xsd:decimal) | 2004-01-01T00:00:00Z (xsd:dateTime) |

[Assistant] I'll execute a SPARQL query that finds the Wikidata item with ROR ID "024z2rq82", retrieves all P2196 (count of students) statements with a point in time (P585), groups by year, and returns one representative student count per year (using MAX in case multiple slightly different counts exist for the same year). I'll order the results by year. Now I'll run the query.

[Tool]
Got 24 rows and 4 columns, showing the first 5 and last 5 rows below:
| org                                   | orgLabel                      | year           | students            |
| ------------------------------------- | ----------------------------- | -------------- | ------------------- |
| University of Düsseldorf (wd:Q317032) | University of Düsseldorf (en) | 1998 (xsd:int) | 23997 (xsd:decimal) |
| University of Düsseldorf (wd:Q317032) | University of Düsseldorf (en) | 1999 (xsd:int) | 24789 (xsd:decimal) |
| University of Düsseldorf (wd:Q317032) | University of Düsseldorf (en) | 2000 (xsd:int) | 24868 (xsd:decimal) |
| University of Düsseldorf (wd:Q317032) | University of Düsseldorf (en) | 2001 (xsd:int) | 25537 (xsd:decimal) |
| University of Düsseldorf (wd:Q317032) | University of Düsseldorf (en) | 2002 (xsd:int) | 25220 (xsd:decimal) |
| ...                                   | ...                           | ...            | ...                 |
| University of Düsseldorf (wd:Q317032) | University of Düsseldorf (en) | 2017 (xsd:int) | 35343 (xsd:decimal) |
| University of Düsseldorf (wd:Q317032) | University of Düsseldorf (en) | 2018 (xsd:int) | 36575 (xsd:decimal) |
| University of Düsseldorf (wd:Q317032) | University of Düsseldorf (en) | 2019 (xsd:int) | 37540 (xsd:decimal) |
| University of Düsseldorf (wd:Q317032) | University of Düsseldorf (en) | 2020 (xsd:int) | 36070 (xsd:decimal) |
| University of Düsseldorf (wd:Q317032) | University of Düsseldorf (en) | 2021 (xsd:int) | 33942 (xsd:decimal) |

[Assistant] The query returned counts per year for University of Düsseldorf. I will now produce the final SPARQL query (which returns the item IRIs and year and student counts) and provide the answer listing the student counts per year, ordered by year. According to the additional rules, I must explain my thought process before and after each function call — I've done that. Now I'll call the answer function with the final query and the summarized results.

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX xsd: <http://www.w3.org/2001/XMLSchema#>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?item ?label ?number WHERE {
  ?item wdt:P16 wd:Q1967342 .
  ?item rdfs:label ?label .
  FILTER ( LANG( ?label ) = "en" ) .
  FILTER ( REGEX( STR( ?label ) , "^National Highway " ) ) .
  BIND( xsd:integer ( REPLACE( STR( ?label ) , "[^0-9]" , "" ) ) AS ?number ) FILTER ( ?number < 100 )
}
ORDER BY ?number

Got 83 rows and 3 columns, showing the first 5 and last 5 rows below:
| item                               | label                    | number       |
| ---------------------------------- | ------------------------ | ------------ |
| National Highway 1 (wd:Q642922)    | National Highway 1 (en)  | 1 (xsd:int)  |
| National Highway 2 (wd:Q25203036)  | National Highway 2 (en)  | 2 (xsd:int)  |
| National Highway 3 (wd:Q25203039)  | National Highway 3 (en)  | 3 (xsd:int)  |
| National Highway 4 (wd:Q6973185)   | National Highway 4 (en)  | 4 (xsd:int)  |
| National Highway 5 (wd:Q25203045)  | National Highway 5 (en)  | 5 (xsd:int)  |
| ...                                | ...                      | ...          |
| National Highway 79 (wd:Q25203074) | National Highway 79 (en) | 79 (xsd:int) |
| National Highway 81 (wd:Q25352382) | National Highway 81 (en) | 81 (xsd:int) |
| National Highway 83 (wd:Q25212186) | National Highway 83 (en) | 83 (xsd:int) |
| National Highway 85 (wd:Q25207402) | National Highway 85 (en) | 85 (xsd:int) |
| National Highway 87 (wd:Q24238723) | National Highway 87 (en) | 87 (xsd:int) |

I ran a query that finds items which are part of the "national highways of India" transport network (wd:Q1967342), returns their English labels, extracts the numeric highway number from the label, filters for numbers less than 100, and orders by the number. The query returns 83 highways. The SPARQL query is provided above and when executed returns the item IRIs, English labels, and the extracted highway numbers ordered by highway number.

What are the Indian National Highways that are part of the national highways of India transport network? Return also their English labels and highway numbers (extracted from the labels), only include highways with numbers less than 100, and order by highway number.

[System]
You are a question answering assistant. Your job is to generate a SPARQL query to answer a given user question.

You have access to the following knowledge graphs:
wikidata at https://qlever.cs.uni-freiburg.de/api/wikidata-sebastian

You are provided with some general notes:
No notes available

You can use the following SPARQL prefixes implicitly in all functions:
cc: <http://creativecommons.org/ns#
data: <https://www.wikidata.org/wiki/Special:EntityData/
dct: <http://purl.org/dc/terms/
geo: <http://www.opengis.net/ont/geosparql#
geof: <http://www.opengis.net/def/function/geosparql/
imdb: <https://www.imdb.com/
math: <http://www.w3.org/2005/xpath-functions/math#
ontolex: <http://www.w3.org/ns/lemon/ontolex#
owl: <http://www.w3.org/2002/07/owl#
p: <http://www.wikidata.org/prop/
pq: <http://www.wikidata.org/prop/qualifier/
pqn: <http://www.wikidata.org/prop/qualifier/value-normalized/
pqv: <http://www.wikidata.org/prop/qualifier/value/
pr: <http://www.wikidata.org/prop/reference/
prn: <http://www.wikidata.org/prop/reference/value-normalized/
prov: <http://www.w3.org/ns/prov#
prv: <http://www.wikidata.org/prop/reference/value/
ps: <http://www.wikidata.org/prop/statement/
psn: <http://www.wikidata.org/prop/statement/value-normalized/
psv: <http://www.wikidata.org/prop/statement/value/
qfn: <http://qlever.cs.uni-freiburg.de/function#
ql: <http://qlever.cs.uni-freiburg.de/builtin-functions/
qlss: <https://qlever.cs.uni-freiburg.de/spatialSearch/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
ref: <http://www.wikidata.org/reference/
s: <http://www.wikidata.org/entity/statement/
schema: <http://schema.org/
skos: <http://www.w3.org/2004/02/skos/core#
v: <http://www.wikidata.org/value/
wd: <http://www.wikidata.org/entity/
wdno: <http://www.wikidata.org/prop/novalue/
wdt: <http://www.wikidata.org/prop/direct/
wdtn: <http://www.wikidata.org/prop/direct-normalized/
wikibase: <http://wikiba.se/ontology#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
dc: <http://purl.org/dc/elements/1.1/
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
qb: <http://purl.org/linked-data/cube#
void: <http://rdfs.org/ns/void#

You should follow a step-by-step approach to generate the SPARQL query:
1. Determine possible entities and properties implied by the user question.
2. Search for the entities and properties in the knowledge graphs. Where applicable, constrain the searches with already identified entities and properties.
3. Gradually build up the SPARQL query using the identified entities and properties. Start with simple queries and add more complexity as needed. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

Additional rules:
1. Explain your thought process before and after each step and function call.
2. Do not just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
3. Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
4. The SPARQL query should always return the actual identifiers / IRIs of the items in its result. It additionally may return labels or other human-readable information, but they are optional and should be put within optional clauses unless explicitly requested by the user.
5. Do not stop early if there are still obvious improvements to be made to the SPARQL query. For example, keep refining your SPARQL query if its result contains irrelevant items or is missing items you expected.
6. Do not perform additional computation (e.g. filtering, sorting, calculations) on the result of the SPARQL query to determine the answer. All computation should be done solely within SPARQL.
7. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
8. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] What are the Indian National Highways that are part of the national highways of India transport network? Return also their English labels and highway numbers (extracted from the labels), only include highways with numbers less than 100, and order by highway number.

[Assistant] Step 1: I'll search for the Wikidata item representing the "national highways of India" transport network. Then I'll find highways that are part of that network and filter by highway numbers less than 100 (extracting the number from labels). I'll start by searching for the network entity.

[Tool]
Top 10 entity alternatives:
1. national highways of India, also known as India's National Highways, National Highways of India, National Highway (wd:Q1967342)
2. National Highways Authority of India, also known as NHAI (wd:Q282114): Agency responsible for Road Construction and It's Management in India, instance of government agency, instance of organization
3. National Highways Authority of India Act, 1988 (wd:Q95338787): instance of Act of the Parliament of India, Act of the Parliament of India
4. National Highways Authority of India (Amendment) Act, 2013 (wd:Q79471774): instance of Act of the Parliament of India, Act of the Parliament of India, instance of amendment
5. Roadkill animals on national highways of Karnataka, India (wd:Q125952091): scientific article published in 2012, instance of scholarly article
6. National Library of India (wd:Q619913): national library located in Kolkata, instance of national library
7. national park of India, also known as Indian National Parks and Wildlife Sanctuaries (wd:Q1125269)
8. National Museum, also known as National Museum of India, National Museum, New Delhi (wd:Q1356138): National and art museum in New Delhi, India, instance of national museum, instance of art museum
9. National symbols of India (wd:Q3536434)
10. National Archives of India (wd:Q6970437): Official Archive of the Government of India, instance of national archives

[Assistant] Now I'll inspect the Wikidata item wd:Q1967342 to find how highways link to it (which property is used).

[Tool]
Got 122 rows and 3 columns, showing the first 10 rows below:
| subject                                  | property                         | object                                                                                |
| ---------------------------------------- | -------------------------------- | ------------------------------------------------------------------------------------------------------------------------------ |
| national highways of India (wd:Q1967342) | instance of (wdt:P31)            | highway system (wd:Q25631158)                                                                                |
| national highways of India (wd:Q1967342) | country (wdt:P17)                | India (wd:Q668)                                                                                |
| national highways of India (wd:Q1967342) | Commons category (wdt:P373)      | National highways in India                                                                                |
| national highways of India (wd:Q1967342) | subclass of (wdt:P279)           | road (wd:Q34442)                                                                                |
| national highways of India (wd:Q1967342) | topic's main category (wdt:P910) | wd:Q8544530                                                                                |
| national highways of India (wd:Q1967342) | maintained by (wdt:P126)         | National Highways Authority of India (wd:Q282114)                                                                              |
| national highways of India (wd:Q1967342) | transport network (wdt:P16)      | roads in India (wd:Q3537728)                                                                                |
| national highways of India (wd:Q1967342) | has list (wdt:P2354)             | wd:Q19893264                                                                                |
| national highways of India (wd:Q1967342) | traffic sign (wdt:P14)           | <http://commons.wikimedia.org/wiki/Special:FilePath/Road%20marker%20IN%20NH.svg>                                               |
| national highways of India (wd:Q1967342) | route map (wdt:P15)              | <http://commons.wikimedia.org/wiki/Special:FilePath/Renumbered%20National%20Highways%20map%20of%20India%20%28Schematic%29.jpg> |
| ...                                      | ...                              | ...                                                                                |

[Assistant] We need items that are Indian National Highways that are part of the national highways of India transport network. Likely individual highways have property 'part of' (wdt:P361) or 'part of the network' (wdt:P126? no). Let's search for items that are instance of 'national highway of India' or subclass of 'national highway of India'. I'll search for properties linking highways to the network: search for items with 'part of' wd:Q1967342.

[Tool]
Top 10 property alternatives:
1. part of, also known as meronym of, contained within, of, part of-property, section of (wd:P361 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): object of which the subject is a part (if this subject is alread... of "has part" (P527, see also "has parts of the class" (P2670))
2. parent organization, also known as parent company, parent institution, parent organisation, parent unit, part of (wd:P749 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): parent organization of an organization, opposite of subsidiaries (P355), subproperty of owned by, subproperty of part of
3. partially coincident with, also known as partially include, overlaps, partially in, partial concurrency, overlaps with (wd:P1382 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): object that partially overlaps with the subject in its instances, parts, or members, subproperty of different from
4. applies to part, also known as applies to aspect, applied to, when viewed as, valid for part, section (wd:P518 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): part, aspect, or form of the item to which the claim applies
5. proportion, also known as %, part, percent, ratio, share (wd:P1107 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): to be used as a qualifier, value must be between 0 and 1
6. has part(s), also known as has ingredient, has ingredients, had part, has member, has part (wd:P527 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): part of this subject; inverse property of "part of" (P361). See also "has parts of the class" (P2670).
7. located in the present-day administrative territorial entity, also known as present-day administrative territorial entity, located in the current administrative territorial entity, located in the modern-day administrative territorial entity, located in the present-day administrative territorial entity, located in present day administrative territorial entity (wd:P3842 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): the item was located in the territory of this present-day administrative unit; however the two did not at any point coexist in time, subproperty of location, subproperty of part of
8. depicted part, also known as part depicted, part shown, shown part (wd:P5961 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): use as qualifier for "depicts" (P180)
9. based on, also known as modelled after, inspired by, iteration of, modeled after, input (wd:P144 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): the work(s) or inputs used as the basis for subject item; for fictional analog use P1074, subproperty of references work, tradition or theory, subproperty of inspired by
10. territory overlaps, also known as partially located in territorial entity, partly overlaps, partly located in territorial entity, partly coincident with, partially overlaps (wd:P3179 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): part or all of the area associated with (this) entity overlaps part or all of the area associated with that entity, subproperty of partially coincident with

[Assistant] I'll search for highways (items) that have property wdt:P361 (part of) with object wd:Q1967342.

[Tool] Got no rows and 3 columns

[Tool]
Got 652 rows and 3 columns, showing the first 10 rows below:
| subject                                         | property                    | object                                   |
| ----------------------------------------------- | --------------------------- | ---------------------------------------- |
| Raipur–Visakhapatnam Expressway (wd:Q104848629) | transport network (wdt:P16) | national highways of India (wd:Q1967342) |
| National Highway 109K (wd:Q105759673)           | transport network (wdt:P16) | national highways of India (wd:Q1967342) |
| National Highway 148A (wd:Q106647823)           | transport network (wdt:P16) | national highways of India (wd:Q1967342) |
| National Highway 229 (wd:Q106652354)            | transport network (wdt:P16) | national highways of India (wd:Q1967342) |
| National Highway 753AB (wd:Q106668254)          | transport network (wdt:P16) | national highways of India (wd:Q1967342) |
| National Highway 744A (wd:Q106668587)           | transport network (wdt:P16) | national highways of India (wd:Q1967342) |
| National Highway 948A (wd:Q106668782)           | transport network (wdt:P16) | national highways of India (wd:Q1967342) |
| National Highway 530B (wd:Q106669240)           | transport network (wdt:P16) | national highways of India (wd:Q1967342) |
| National Highway 179B (wd:Q106669683)           | transport network (wdt:P16) | national highways of India (wd:Q1967342) |
| National Highway 179D (wd:Q106670027)           | transport network (wdt:P16) | national highways of India (wd:Q1967342) |
| ...                                             | ...                         | ...                                      |

[Assistant] I'll search for a Wikidata class for "national highway" or "national highway in India" to better filter highway items.

[Tool]
Top 10 entity alternatives:
1. national highways of India, also known as India's National Highways, National Highways of India, National Highway (wd:Q1967342)
2. National Highways Authority of India, also known as NHAI (wd:Q282114): Agency responsible for Road Construction and It's Management in India, instance of government agency, instance of organization
3. National Highways Authority of India Act, 1988 (wd:Q95338787): instance of Act of the Parliament of India, Act of the Parliament of India
4. National Highways Authority of India (Amendment) Act, 2013 (wd:Q79471774): instance of Act of the Parliament of India, Act of the Parliament of India, instance of amendment
5. State Bank of India, Suryapet National Highway Road branch (wd:Q65959983): instance of State Bank of India branch
6. Roadkill animals on national highways of Karnataka, India (wd:Q125952091): scientific article published in 2012, instance of scholarly article
7. National Library of India (wd:Q619913): national library located in Kolkata, instance of national library
8. national park of India, also known as Indian National Parks and Wildlife Sanctuaries (wd:Q1125269)
9. National Museum, also known as National Museum of India, National Museum, New Delhi (wd:Q1356138): National and art museum in New Delhi, India, instance of national museum, instance of art museum
10. National symbols of India (wd:Q3536434)

[Assistant] I'll inspect one of the highway items from the transport network list to see how labels are formed and properties available. I'll pick National Highway 229 (wd:Q106652354).

[Tool]
Got 33 rows and 3 columns, showing the first 10 rows below:
| subject                              | property                                                    | object                                                            |
| ------------------------------------ | ----------------------------------------------------------- | ----------------------------------------------------------------- |
| National Highway 229 (wd:Q106652354) | instance of (wdt:P31)                                       | road (wd:Q34442)                                                  |
| National Highway 229 (wd:Q106652354) | country (wdt:P17)                                           | India (wd:Q668)                                                   |
| National Highway 229 (wd:Q106652354) | located in the administrative territorial entity (wdt:P131) | Nagaland (wd:Q1599)                                               |
| National Highway 229 (wd:Q106652354) | owned by (wdt:P127)                                         | Ministry of Road Transport and Highways (wd:Q167156)              |
| National Highway 229 (wd:Q106652354) | transport network (wdt:P16)                                 | national highways of India (wd:Q1967342)                          |
| National Highway 229 (wd:Q106652354) | terminus (wdt:P559)                                         | National Highway 29 (wd:Q6973212)                                 |
| National Highway 229 (wd:Q106652354) | road number (wdt:P1824)                                     | NH 229                                                            |
| National Highway 229 (wd:Q106652354) | terminus location (wdt:P609)                                | Dimapur (wd:Q867111)                                              |
| National Highway 229 (wd:Q106652354) | traffic sign (wdt:P14)                                      | <http://commons.wikimedia.org/wiki/Special:FilePath/NH229-IN.svg> |
| National Highway 229 (wd:Q106652354) | Gazette of India notification (wdt:P8206)                   | S.O. 2573 (E) dated 28 July 2016                                  |
| ...                                  | ...                                                         | ...                                                               |

[Assistant] I'll run a first SPARQL query to list items that are part of the national highways of India (wd:Q1967342) and have an English label containing digits, to inspect label formats.

[Tool]
Got 100 rows and 2 columns, showing the first 5 and last 5 rows below:
| item                                   | label                       |
| -------------------------------------- | --------------------------- |
| National Highway 109K (wd:Q105759673)  | National Highway 109K (en)  |
| National Highway 148A (wd:Q106647823)  | National Highway 148A (en)  |
| National Highway 229 (wd:Q106652354)   | National Highway 229 (en)   |
| National Highway 753AB (wd:Q106668254) | National Highway 753AB (en) |
| National Highway 744A (wd:Q106668587)  | National Highway 744A (en)  |
| ...                                    | ...                         |
| National Highway 325 (wd:Q18619665)    | National Highway 325 (en)   |
| National Highway 502 (wd:Q18619667)    | National Highway 502 (en)   |
| National Highway 507 (wd:Q18619668)    | National Highway 507 (en)   |
| National Highway 509 (wd:Q18619669)    | National Highway 509 (en)   |
| National Highway 515 (wd:Q18619670)    | National Highway 515 (en)   |

[Assistant] I'll run a SPARQL query that finds items with transport network = national highways of India, gets their English label, extracts the first consecutive digits from the label as the highway number using REPLACE, filters numbers < 100, and orders by that number. Now I'll execute the query to see the results.

[Tool]
Got 648 rows and 3 columns, showing the first 5 and last 5 rows below:
| item                                  | label                      | number        |
| ------------------------------------- | -------------------------- | ------------- |
| National Highway 1 (wd:Q642922)       | National Highway 1 (en)    | 1 (xsd:int)   |
| National Highway 2 (wd:Q25203036)     | National Highway 2 (en)    | 2 (xsd:int)   |
| National Expressway 3 (wd:Q19891290)  | National Expressway 3 (en) | 3 (xsd:int)   |
| National Highway 3 (wd:Q25203039)     | National Highway 3 (en)    | 3 (xsd:int)   |
| National Expressway 4 (wd:Q106687519) | National Expressway 4 (en) | 4 (xsd:int)   |
| ...                                   | ...                        | ...           |
| National Highway 965 (wd:Q55473678)   | National Highway 965 (en)  | 965 (xsd:int) |
| National Highway 966 (wd:Q6973174)    | National Highway 966 (en)  | 966 (xsd:int) |
| National Highway 966B (wd:Q18619678)  | National Highway 966B (en) | 966 (xsd:int) |
| National Highway 966A (wd:Q18627423)  | National Highway 966A (en) | 966 (xsd:int) |
| National Highway 968 (wd:Q106678243)  | National Highway 968 (en)  | 968 (xsd:int) |

[Assistant] Now I'll execute the final SPARQL query that selects items in the national highways of India transport network whose English label starts with "National Highway", extracts the numeric part from the label, filters numbers < 100, and orders by the extracted number.

[Tool]
SPARQL execution failed:
Invalid SPARQL query: Escaping the character s is not allowed in QLever's regex filters. (Regex was ^National Highway\s*\d) Please note that there are two levels of escaping in place here: One for SPARQL and one for the regex engine

[Assistant] I'll run a corrected SPARQL query that matches English labels starting with "National Highway " followed by digits, extracts the digits using REPLACE, filters for numbers < 100, and orders by that number. Now I execute the query.

[Tool]
Call to function execute returned an error:
failed to parse input: no matching token found from position 54: '"^National Highway (\\\d+).*$", "$1")) AS ?number) WHERE {
  ?item wdt:P16 wd:Q1967342 .
  ?item rdfs:label ?label .
  FILTER(LANG(?label) = "en") .
  FILTER(REGEX(STR(?label), "^National Highway [0-9]")) .
  BIND(xsd:integer(REPLACE(STR(?label), "^National Highway (\\\d+).*$", "$1")) AS ?number)
  FILTER(?number < 100)
} ORDER BY ?number'

[Tool]
SPARQL execution failed:
Invalid SPARQL query: The target ?number of an AS clause was already used in the query body.

[Assistant] I'll run a SPARQL query that selects items in the national highways of India transport network (wd:Q1967342) with English labels starting with "National Highway ", extracts all digits from the label to form the highway number, filters numbers less than 100, and orders by that number. I'll execute it to get the actual results.

[Tool]
Got 83 rows and 3 columns, showing the first 5 and last 5 rows below:
| item                               | label                    | num          |
| ---------------------------------- | ------------------------ | ------------ |
| National Highway 1 (wd:Q642922)    | National Highway 1 (en)  | 1 (xsd:int)  |
| National Highway 2 (wd:Q25203036)  | National Highway 2 (en)  | 2 (xsd:int)  |
| National Highway 3 (wd:Q25203039)  | National Highway 3 (en)  | 3 (xsd:int)  |
| National Highway 4 (wd:Q6973185)   | National Highway 4 (en)  | 4 (xsd:int)  |
| National Highway 5 (wd:Q25203045)  | National Highway 5 (en)  | 5 (xsd:int)  |
| ...                                | ...                      | ...          |
| National Highway 79 (wd:Q25203074) | National Highway 79 (en) | 79 (xsd:int) |
| National Highway 81 (wd:Q25352382) | National Highway 81 (en) | 81 (xsd:int) |
| National Highway 83 (wd:Q25212186) | National Highway 83 (en) | 83 (xsd:int) |
| National Highway 85 (wd:Q25207402) | National Highway 85 (en) | 85 (xsd:int) |
| National Highway 87 (wd:Q24238723) | National Highway 87 (en) | 87 (xsd:int) |

[Assistant] The query returned 83 highways with numbers less than 100. I'll prepare the final SPARQL query to return the item IRIs, English labels, and the extracted highway number, ordered by highway number. Then I'll provide the answer, noting that the query returns 83 items.

[Tool] Stopped generation process


Failed to answer the question

What are the institutions located in municipalities or cantons of Switzerland that are described in Memobase? Include their types (if available), street addresses (if available), municipalities (if available), and cantons (if available). Exclude any institutions where the municipality is within the canton, as well as institutions that no longer exist. Order results by item ID.

[System]
You are a question answering assistant. Your job is to generate a SPARQL query to answer a given user question.

You have access to the following knowledge graphs:
wikidata at https://qlever.cs.uni-freiburg.de/api/wikidata-sebastian

You are provided with some general notes:
No notes available

You can use the following SPARQL prefixes implicitly in all functions:
cc: <http://creativecommons.org/ns#
data: <https://www.wikidata.org/wiki/Special:EntityData/
dct: <http://purl.org/dc/terms/
geo: <http://www.opengis.net/ont/geosparql#
geof: <http://www.opengis.net/def/function/geosparql/
imdb: <https://www.imdb.com/
math: <http://www.w3.org/2005/xpath-functions/math#
ontolex: <http://www.w3.org/ns/lemon/ontolex#
owl: <http://www.w3.org/2002/07/owl#
p: <http://www.wikidata.org/prop/
pq: <http://www.wikidata.org/prop/qualifier/
pqn: <http://www.wikidata.org/prop/qualifier/value-normalized/
pqv: <http://www.wikidata.org/prop/qualifier/value/
pr: <http://www.wikidata.org/prop/reference/
prn: <http://www.wikidata.org/prop/reference/value-normalized/
prov: <http://www.w3.org/ns/prov#
prv: <http://www.wikidata.org/prop/reference/value/
ps: <http://www.wikidata.org/prop/statement/
psn: <http://www.wikidata.org/prop/statement/value-normalized/
psv: <http://www.wikidata.org/prop/statement/value/
qfn: <http://qlever.cs.uni-freiburg.de/function#
ql: <http://qlever.cs.uni-freiburg.de/builtin-functions/
qlss: <https://qlever.cs.uni-freiburg.de/spatialSearch/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
ref: <http://www.wikidata.org/reference/
s: <http://www.wikidata.org/entity/statement/
schema: <http://schema.org/
skos: <http://www.w3.org/2004/02/skos/core#
v: <http://www.wikidata.org/value/
wd: <http://www.wikidata.org/entity/
wdno: <http://www.wikidata.org/prop/novalue/
wdt: <http://www.wikidata.org/prop/direct/
wdtn: <http://www.wikidata.org/prop/direct-normalized/
wikibase: <http://wikiba.se/ontology#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
dc: <http://purl.org/dc/elements/1.1/
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
qb: <http://purl.org/linked-data/cube#
void: <http://rdfs.org/ns/void#

You should follow a step-by-step approach to generate the SPARQL query:
1. Determine possible entities and properties implied by the user question.
2. Search for the entities and properties in the knowledge graphs. Where applicable, constrain the searches with already identified entities and properties.
3. Gradually build up the SPARQL query using the identified entities and properties. Start with simple queries and add more complexity as needed. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

Additional rules:
1. Explain your thought process before and after each step and function call.
2. Do not just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
3. Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
4. The SPARQL query should always return the actual identifiers / IRIs of the items in its result. It additionally may return labels or other human-readable information, but they are optional and should be put within optional clauses unless explicitly requested by the user.
5. Do not stop early if there are still obvious improvements to be made to the SPARQL query. For example, keep refining your SPARQL query if its result contains irrelevant items or is missing items you expected.
6. Do not perform additional computation (e.g. filtering, sorting, calculations) on the result of the SPARQL query to determine the answer. All computation should be done solely within SPARQL.
7. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
8. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] What are the institutions located in municipalities or cantons of Switzerland that are described in Memobase? Include their types (if available), street addresses (if available), municipalities (if available), and cantons (if available). Exclude any institutions where the municipality is within the canton, as well as institutions that no longer exist. Order results by item ID.

[Assistant] Step 1: I'll search for the "Memobase" entity in Wikidata to find its identifier. Then I'll look for items that have descriptions or references to Memobase. I'll start by searching for the entity "Memobase".

[Tool]
Top 10 entity alternatives:
1. Memobase (wd:Q96192978): portal and database of Swiss multimedia heritage content managed by Memoriav, instance of archives portal, instance of web portal, instance of catalogue, instance of database
2. Memobase ID, also known as Memobase identifier, Memobase Object ID (wd:P9657): identifier in the Memobase database of Swiss audiovisual heritage, instance of Wikidata property to identify television shows, instance of Wikidata property to identify radio programs, instance of Wikidata property to identify films

[Assistant] I'll list items that use the Memobase identifier property P9657 to see how it's used and find candidate institutions.

[Tool]
Got 8 rows and 3 columns:
| subject                                            | property                | object                                          |
| -------------------------------------------------- | ----------------------- | ----------------------------------------------- |
| Hermann Huber (wd:Q1611548)                        | Memobase ID (wdt:P9657) | srf-027-SRDRSSRF_242059                         |
| Aargauer Kunsthaus (wd:Q301250)                    | Memobase ID (wdt:P9657) | kha                                             |
| Video 50 (wd:Q100437060)                           | Memobase ID (wdt:P9657) | khz-001-1980_0004                               |
| Out of Sync II (wd:Q100437182)                     | Memobase ID (wdt:P9657) | khz-001-1998_0048                               |
| Fünf Dörfer in Angst (wd:Q107133915)               | Memobase ID (wdt:P9657) | srf-001-53E9D714-FEA4-4D71-94DE-D66CEBCA9E6C_01 |
| Pillenknick (wd:Q107134361)                        | Memobase ID (wdt:P9657) | srf-001-17B9E6BC-7707-4AFF-BC49-164D4C1F2AEB_01 |
| Michèle Roten, Miss Universum (wd:Q107134571)      | Memobase ID (wdt:P9657) | rxb-003-DE3D4EAE6BBA21251422F100F_MPG           |
| Nach der Katastrophe von Wädenswil (wd:Q107135115) | Memobase ID (wdt:P9657) | bar-001-SFW_0329-1                              |

[Assistant] I'll search for properties related to "described in Memobase" and other descriptors to find which property links items to Memobase descriptions.

[Tool]
Top 10 property alternatives:
1. Memobase ID, also known as Memobase identifier, Memobase Object ID (wd:P9657 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): identifier in the Memobase database of Swiss audiovisual heritage
2. year of publication of scientific name for taxon, also known as taxon year, year of scientific description, taxon date, described in, date of taxon description publication (wd:P574 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): year when this taxon was formally described (for animals); year when this taxon name was formally established (for plants), subproperty of publication date
3. described by source, also known as mentioned in, mentioned in news article, reviewed in, source of item, subject in (wd:P1343 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): work where this item is described, subproperty of attested in
4. man page, also known as described in man page, manual page (wd:P11292 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): man page that describes the subject
5. statement describes, also known as statement about (wd:P2384 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): formalization of the statement contains a bound variable in this class
6. described at URL, also known as d@url, descURL, discussed at URL, info URL, mentioned at URL (wd:P973 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): item is described at the following URL, subproperty of URL
7. main subject, also known as main topic, primary subject, primary keyword, plot keyword, of (wd:P921 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): primary topic of a work, subproperty of depicts
8. documentation files at, also known as documentary records at, pamphlet files at, has documentation files at, ephemera files held by, ephemera files held at (wd:P10527 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): institution that holds documentation files about the subject
9. applicable 'stated in' value, also known as applicable database, stated in value, 'stated in' value, stated in database, corresponding P248 value (wd:P9073 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): value suitable for "stated in" (P248) when property is used in r...rimary publication/website/database associated with the property
10. taxon author, also known as described by, author citation, taxon authority (wd:P405 as psv/psn/prn/prv/pqn/p/pq/wdtn/wdt/pqv/ps/pr): the author(s) that (optionally) may be cited with the scientific name

[Assistant]
The property for Memobase ID is P9657. The user asks: "institutions located in municipalities or cantons of Switzerland that are described in Memobase". That likely means items that are instances of some institution and have location in Swiss municipality or canton, and also have a Memobase ID (P9657) or are "described in Memobase" via P1343? The Memobase entity (Q96192978) could be used with P1343 (described by source) or maybe P973 described at URL that points to memobase site. But many items with P9657 are various works, not necessarily institutions. The user specifically wants institutions located in municipalities or cantons of Switzerland that are described in Memobase. So filter for items that are instance of (P31) some "institution" (or instance of subclass of museum, archive, library, etc.), located in municipality (P131? P131 is located in the administrative territorial entity). Also ensure the administrative entity is in Switzerland — the municipality or canton is of Switzerland. Also exclude institutions where the municipality is within the canton (huh?) The user says "Exclude any institutions where the municipality is within the canton" — That is odd: municipalities are always within cantons. Maybe they mean exclude institutions where municipality is within the canton property? Wait need to parse: "located in municipalities or cantons of Switzerland that are described in Memobase" Maybe they want institutions located either in a municipality of Switzerland or in a canton (i.e., located at cantonal level), but exclude cases where the municipality is within the canton — maybe they want to avoid double-counting? Could be interpreted: If institution has both municipality and canton values, and the municipality is within that canton, exclude the institution. That seems strange. Or maybe they mean exclude institutions where the municipality is within the canton (i.e., not independent municipalities?).

We must ask clarifying question? But instructions require generating queries. Let's attempt to interpret: They want institutions located in municipalities or cantons of Switzerland and described in Memobase; exclude any institutions where the municipality is within the canton — that could mean exclude items where P131 (located in the administrative territorial entity) is a municipality that is located in the canton that is also an administrative territory for that item. Alternatively, they mean exclude items where the municipality is located within the canton — always true. Hmm.

Maybe they intended: Exclude any institutions where the municipality is within the canton (i.e., where the municipality is part of the canton), which would exclude all items that have both municipality and canton specified, leaving only those that have canton only? Ambiguous.

We must follow "Additional rules: Explain your thought process before and after each step and function call." So need to narrate steps.

Plan: First find Memobase entity Q96192978. Then find items that have property indicating "described by" P1343 with value Memobase or have Memobase ID P9657. The search earlier found P9657 used on 8 items, but those are media works. But maybe institutions have P9657 too; list all items with P9657 returned 8 only. So maybe there are few. Alternatively, items could have stated in (P248) pointing to Memobase (Q96192978) or described by source (P1343) with Memobase. Let's search for items that have P1343 Memobase.
I'll search for items that have property 'described by source' (P1343) with value Memobase (Q96192978), and also items that have 'stated in' (P248) with Memobase. I'll first verify the Memobase entity Q96192978.

[Tool]
Got 66 rows and 3 columns, showing the first 10 rows below:
| subject                 | property                                  | object                                |
| ----------------------- | ----------------------------------------- | ------------------------------------- |
| Memobase (wd:Q96192978) | instance of (wdt:P31)                     | database (wd:Q8513)                   |
| Memobase (wd:Q96192978) | country (wdt:P17)                         | Switzerland (wd:Q39)                  |
| Memobase (wd:Q96192978) | inception (wdt:P571)                      | 2000-01-01T00:00:00Z (xsd:dateTime)   |
| Memobase (wd:Q96192978) | official website (wdt:P856)               | <https://memobase.ch>                 |
| Memobase (wd:Q96192978) | owned by (wdt:P127)                       | Memoriav (wd:Q1365781)                |
| Memobase (wd:Q96192978) | operator (wdt:P137)                       | Memoriav (wd:Q1365781)                |
| Memobase (wd:Q96192978) | maintained by (wdt:P126)                  | Basel University Library (wd:Q683842) |
| Memobase (wd:Q96192978) | collection or exhibition size (wdt:P1436) | 209 (xsd:decimal)                     |
| Memobase (wd:Q96192978) | Wikidata property (wdt:P1687)             | Memobase ID (wd:P9657)                |
| Memobase (wd:Q96192978) | number of records (wdt:P4876)             | 150000 (xsd:decimal)                  |
| ...                     | ...                                       | ...                                   |

[Assistant] Now I'll search for items that have P1343 (described by source) with Memobase as the value.

[Tool]
Got 82 rows and 3 columns, showing the first 10 rows below:
| subject                                                                        | property                        | object                  |
| ------------------------------------------------------------------------------ | ------------------------------- | ----------------------- |
| International Committee of the Red Cross (wd:Q5987345)                         | described by source (wdt:P1343) | Memobase (wd:Q96192978) |
| International Federation of Red Cross and Red Crescent Societies (wd:Q1069175) | described by source (wdt:P1343) | Memobase (wd:Q96192978) |
| Swiss National Library (wd:Q201787)                                            | described by source (wdt:P1343) | Memobase (wd:Q96192978) |
| Kunsthaus Zürich (wd:Q685038)                                                  | described by source (wdt:P1343) | Memobase (wd:Q96192978) |
| National Museum Zurich (wd:Q691896)                                            | described by source (wdt:P1343) | Memobase (wd:Q96192978) |
| Radiotelevisiun Svizra Rumantscha (wd:Q688243)                                 | described by source (wdt:P1343) | Memobase (wd:Q96192978) |
| Radio télévision suisse (wd:Q3416973)                                          | described by source (wdt:P1343) | Memobase (wd:Q96192978) |
| Swiss Federal Archives (wd:Q679141)                                            | described by source (wdt:P1343) | Memobase (wd:Q96192978) |
| Swiss Museum of Transport (wd:Q670595)                                         | described by source (wdt:P1343) | Memobase (wd:Q96192978) |
| Radiotelevisione svizzera di lingua italiana (wd:Q114794)                      | described by source (wdt:P1343) | Memobase (wd:Q96192978) |
| ...                                                                            | ...                             | ...                     |

[Assistant] I'll search for the Wikidata item for "institution" to use it as a class filter.

[Tool]
Top 10 entity alternatives:
1. organization, also known as organisations, organization in sociology, organisation, organizations, institution (wd:Q43229)
2. institution, also known as social institution, social institutions (wd:Q178706)
3. institution (wd:Q3917196)
4. Institution (wd:Q6041045): notion in computer science
5. Institution (wd:Q59507540): painting by Christopher Pratt, instance of painting
6. institution (wd:L25381-S1)
7. institution (wd:L1147)
8. institution (wd:L1147-F1)
9. institution (wd:L1359751-S1)
10. institution (wd:L1374974-S1)

[Assistant]
The class 'organization' (Q43229) or 'institution' (Q178706) could be used. Many cultural institutions are instance of 'museum' or 'archive' etc. I'll craft a SPARQL query to retrieve items that have P1343 Memobase and that are instance of organization or subclass thereof, and have location P131 pointing to an admin entity that is a municipality or canton in Switzerland. Also retrieve types (P31), street address (P6375? no, street address is P969? Wait check). Street address property in Wikidata is "street address" P969. Municipality property: located in the administrative territorial entity P131. Canton property maybe present as "located in the administrative territorial entity" also pointing to a canton. Or there is property "located in the canton" P??? There's "located in the administrative territorial entity" P131 and "located in the administrative territorial entity" can point to municipality or canton. Also there's "cantonal location" no. So we should extract P131 chain and then find if that admin entity has instance of 'municipality of Switzerland' Q?? or 'canton of Switzerland' Q?? Let's find entities for Swiss municipality and canton.

Search for "municipality of Switzerland" and "canton of Switzerland".

[Tool]
Top 10 entity alternatives:
1. municipality of Switzerland, also known as communes of Switzerland, politische Gemeinde, commune of Switzerland (wd:Q70208)
2. municipality of Switzerland (wd:L25865-S1)
3. former municipality of Switzerland (wd:Q685309)
4. former municipality of Switzerland (wd:L26070-S1)
5. former municipality of Switzerland (wd:L25883-S1)
6. former municipality of Switzerland in Fribourg (wd:L25882-S1)
7. former municipality of Switzerland in Vaud (wd:L25869-S1)
8. former municipality of Switzerland in Vaud (wd:L25867-S1)
9. former municipality of Switzerland in Valais (wd:L27709-S1)
10. former municipality of Switzerland in Vaud (wd:L25924-S1)

[Tool]
Top 10 entity alternatives:
1. canton of Switzerland, also known as Swiss canton, Canton of Switzerland, canton (wd:Q23058)
2. Glarus, also known as Glaris, Glarus (Switzerland), Glarus GL, Glarus, Canton of Glarus, Switzerland, Glaris Centre (wd:Q63912): municipality and capital of the Canton of Glarus in Switzerland, instance of cantonal capital of Switzerland, instance of municipality of Switzerland, instance of city of Switzerland
3. Villeneuve, also known as Villeneuve, Canton of Vaud, Switzerland, Villeneuve VD, Villeneuve, Vaud (wd:Q69972): instance of municipality of Switzerland, municipality in Switzerland
4. Reinach, also known as Reinach, Basel-Country, Reinach BL, Reinach, Canton of Basel-Land, Switzerland (wd:Q69747): municipality in the canton of Basel-Country, Switzerland, instance of municipality of Switzerland, instance of city of Switzerland
5. Romont, also known as Romont, Canton of Fribourg, Switzerland, Romont FR (wd:Q67103): municipality in the canton of Fribourg, Switzerland, instance of municipality of Switzerland
6. Aesch, also known as Aesch, Canton of Basel-Land, Switzerland, Aesch BL, Aesch, Baselland, Aesch, Basel-Country (wd:Q68367): municipality in the canton of Basel-Country, Switzerland, instance of municipality of Switzerland, instance of city of Switzerland
7. Kilchberg, also known as Kilchberg, Canton of Zürich, Switzerland, Kilchberg ZH (wd:Q66633): municipality in the canton of Zürich, Switzerland, instance of municipality of Switzerland
8. Ecublens, also known as Écublens, Écublens VD, Ecublens VD, Ecublens (VD), Écublens, Vaud (wd:Q69716): municipality in the canton of Vaud, Switzerland, instance of municipality of Switzerland, instance of city of Switzerland
9. Oberdorf, also known as Oberdorf BL, Oberdorf, Canton of Basel-Land, Switzerland (wd:Q64821): municipality in the canton Basel-Landschaft, Switzerland, instance of municipality of Switzerland
10. Buchs, also known as Buchs, Canton of Aargau, Switzerland, Buchs AG (wd:Q64512): municipality in the canton of Aargau, Switzerland, instance of municipality of Switzerland

[Assistant]
I need a clarification before I build the SPARQL query — one part of your request is ambiguous.

When you say "Exclude any institutions where the municipality is within the canton," do you mean one of the following?

Option A — Exclude items that have both a municipality and a canton recorded, where the municipality is part of that canton (i.e., avoid items that have both municipality and canton values that are hierarchically related). In other words, only keep items that either (1) have only a municipality (no canton given), (2) have only a canton (no municipality given), or (3) have both but the municipality is not located in that canton (rare).

Option B — Exclude items that are located in a municipality (i.e., exclude all items whose location is given at the municipality level). In other words, only include institutions whose location is given at canton level.

Option C — Something else? (Please describe.)

Also confirm how to interpret "described in Memobase": should I treat items as "described in Memobase" when they have either the stated-in/described-by property pointing to Memobase (P1343 = wd:Q96192978) or when they have a Memobase identifier (property P9657)? I can include both cases (P1343 OR P9657), or only P1343, whichever you prefer.

Finally, to exclude institutions that "no longer exist", do you want to exclude items that have any end/dissolution date (e.g., P576 "dissolved, abolished or demolished" or P582 "end time"), or exclude those whose instance is a "former" entity (e.g., instance of "former museum" / "former organisation")? Which criterion do you prefer?

Tell me which options you prefer (A or B for the municipality/canton rule, P1343 vs P9657 vs both for Memobase, and whether to filter by P576/P582 or by 'former' instance), and I'll construct and run the SPARQL query and return results (with explanations of each step).